整合PDX和PDX来源类器官平台以增强乳腺癌的转化药物发现

Breast cancer remains a leading cause of mortality among women, underscoring the need for translational models that more accurately predict clinical response. Traditional immortalized cancer cell lines lack the genetic diversity, three-dimensional architecture, and stromal microenvironmental context of patient tumors, thereby limiting their translational relevance. Patient-derived xenograft (PDX) models preserve the histologic and molecular features of primary breast tumors across passages and have become powerful systems for evaluating therapeutic response, mechanisms of resistance, and biomarker discovery across subtypes including triple-negative, HER2-positive, and hormone receptor-positive cancers. Despite their translational relevance, PDX studies are resource intensive and low throughput. To address these constraints, patient-derived organoids (PDxO) generated from PDX tumors provide an efficient ex vivo platform for early screening and mechanistic assessment. PDxO models preserve genomic fidelity and phenotypic heterogeneity, enabling direct comparison of drug responses between in vitro and in vivo systems. This integrated workflow supports rapid, iterative evaluation in which compounds are first screened in PDxO cultures to assess efficacy, cytotoxicity, and mechanism of action, followed by validation in matched PDX models to confirm pharmacodynamic performance and in vivo antitumor activity. We have established an advanced organoid-based drug discovery platform by leveraging our breast cancer PDX collection to generate robust PDxO models. We developed and validated high-quality organoid drug-screening assays using CellTiter-Glo 3D and real-time live-cell imaging with the Incucyte system, enabling quantitative assessment of viability, growth kinetics, and treatment responses. Using models such as HCI-015 and HCI-032, we demonstrated consistent organoid formation, reproducible drug sensitivity profiling, and applicability across diverse therapeutic modalities, including agents under evaluation for immunotherapy combinations. Collectively, the integrated use of PDX and PDxO platforms enable a more comprehensive understanding of breast cancer biology and therapeutic vulnerabilities. Correlating drug response data across systems reveals model-specific and subtype-dependent differences, facilitating rational treatment selection and biomarker identification. This complementary approach advances precision oncology by linking high-throughput ex vivo screening with biologically relevant in vivo validation, thereby accelerating the translation of preclinical discoveries into actionable clinical strategies.